The FAIR Framework of threats to data quality

ABSTRACT

The purpose of this conceptual article is to document major threats to online survey data quality through the lens of current practices in the marketing research industry. The Fair Framework categorizes threats ranging from respondent misbehavior to criminal activity in the form of survey fraud. Real examples provide evidence of threats by individual humans as well as serious weaknesses undermining the research supply chain infrastructure, especially regarding sampling. This paper offers academic and practitioner researchers detailed knowledge and actionable insights to effectively combat data quality threats and support the development of robust, reliable, and ethical marketing research practices.

Acknowledgement

We thank Mr. Terence R. McCarron, OpinionRoute CEO & Founder, for helpful comments on this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics approvals

The proposal for this research was reviewed and approved by the Institutional Review Board at the authors’ university.

Additional information

Funding

No outside funding was used for the research described in this article.